----------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  /Users/qsg999/Desktop/PSRM_replication_material/Appendix_C_log.log
  log type:  text
 opened on:  18 Jun 2024, 09:08:02

. 
. use "`path'/Data_Appendix_C.dta", clear

. cd "`path'/temp"
/Users/qsg999/Desktop/PSRM_replication_material/temp

. 
.         
.         * Table C1
.         reg dk_estate_tax t_w i.round, cluster(respondent_id)

Linear regression                               Number of obs     =      9,620
                                                F(3, 4809)        =     576.80
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1498
                                                Root MSE          =     .31642

                      (Std. err. adjusted for 4,810 clusters in respondent_id)
------------------------------------------------------------------------------
             |               Robust
dk_estate_~x | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         t_w |   .2654886   .0063824    41.60   0.000     .2529761    .2780011
             |
       round |
          2  |   .0032315   .0082767     0.39   0.696    -.0129947    .0194576
          3  |   -.003654    .007899    -0.46   0.644    -.0191396    .0118317
             |
       _cons |   .0038914   .0049586     0.78   0.433    -.0058298    .0136125
------------------------------------------------------------------------------

.         outreg2 using table_C1,  word  bd(3) sd(3) rd(3) alpha(0.01, 0.05, 0.1) symbol(**, *
> , +)  lab replace
table_C1.rtf
dir : seeout

.         
.         reg dk_estate_tax i.t_w##c.pol_know i.round, cluster(respondent_id)

Linear regression                               Number of obs     =      9,620
                                                F(5, 4809)        =     368.71
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1819
                                                Root MSE          =     .31041

                        (Std. err. adjusted for 4,810 clusters in respondent_id)
--------------------------------------------------------------------------------
               |               Robust
 dk_estate_tax | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------+----------------------------------------------------------------
         1.t_w |   .4397492   .0156302    28.13   0.000     .4091069    .4703915
      pol_know |  -.0017843   .0008016    -2.23   0.026    -.0033558   -.0002129
               |
t_w#c.pol_know |
            1  |  -.0614647   .0046594   -13.19   0.000    -.0705992   -.0523301
               |
         round |
            2  |  -.0003752   .0080972    -0.05   0.963    -.0162495    .0154991
            3  |  -.0088369   .0077712    -1.14   0.256     -.024072    .0063981
               |
         _cons |   .0120192   .0058079     2.07   0.039      .000633    .0234054
--------------------------------------------------------------------------------

.                 outreg2 using table_C1,  word  bd(3) sd(3) rd(3) alpha(0.01, 0.05, 0.1) symb
> ol(**, *, +)  lab append
table_C1.rtf
dir : seeout

.         
.         reg dk_capital_gains t_w i.round, cluster(respondent_id)

Linear regression                               Number of obs     =      9,620
                                                F(3, 4809)        =     246.44
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0703
                                                Root MSE          =     .24668

                      (Std. err. adjusted for 4,810 clusters in respondent_id)
------------------------------------------------------------------------------
             |               Robust
dk_capital~s | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         t_w |   .1349272   .0049624    27.19   0.000     .1251987    .1446557
             |
       round |
          2  |   .0016114   .0066334     0.24   0.808    -.0113931    .0146159
          3  |  -.0131681   .0061375    -2.15   0.032    -.0252004   -.0011358
             |
       _cons |   .0073369   .0039291     1.87   0.062    -.0003659    .0150398
------------------------------------------------------------------------------

.         outreg2 using table_C1,  word  bd(3) sd(3) rd(3) alpha(0.01, 0.05, 0.1) symbol(**, *
> , +)  lab append
table_C1.rtf
dir : seeout

.         
.         reg dk_capital_gains i.t_w##c.pol_know i.round, cluster(respondent_id)

Linear regression                               Number of obs     =      9,620
                                                F(5, 4809)        =     154.79
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0949
                                                Root MSE          =     .24341

                        (Std. err. adjusted for 4,810 clusters in respondent_id)
--------------------------------------------------------------------------------
               |               Robust
dk_capital_g~s | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------+----------------------------------------------------------------
         1.t_w |    .246125   .0130848    18.81   0.000     .2204728    .2717771
      pol_know |  -.0020498   .0007913    -2.59   0.010    -.0036012   -.0004984
               |
t_w#c.pol_know |
            1  |  -.0392213   .0037804   -10.37   0.000    -.0466327     -.03181
               |
         round |
            2  |  -.0007911   .0065444    -0.12   0.904     -.013621    .0120389
            3  |  -.0166206   .0060606    -2.74   0.006    -.0285022   -.0047391
               |
         _cons |   .0151927   .0049228     3.09   0.002     .0055417    .0248437
--------------------------------------------------------------------------------

.                 outreg2 using table_C1,  word  bd(3) sd(3) rd(3) alpha(0.01, 0.05, 0.1) symb
> ol(**, *, +)  lab append
table_C1.rtf
dir : seeout

.         
.         reg dk_abortion t_w i.round, cluster(respondent_id)

Linear regression                               Number of obs     =      9,620
                                                F(3, 4809)        =      61.70
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0175
                                                Root MSE          =     .14215

                      (Std. err. adjusted for 4,810 clusters in respondent_id)
------------------------------------------------------------------------------
             |               Robust
 dk_abortion | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         t_w |   .0378378   .0027831    13.60   0.000     .0323816     .043294
             |
       round |
          2  |   .0026443   .0038817     0.68   0.496    -.0049656    .0102543
          3  |  -.0002904    .003543    -0.08   0.935    -.0072362    .0066555
             |
       _cons |   .0013603   .0023096     0.59   0.556    -.0031675    .0058881
------------------------------------------------------------------------------

.         outreg2 using table_C1,  word  bd(3) sd(3) rd(3) alpha(0.01, 0.05, 0.1) symbol(**, *
> , +)  lab append
table_C1.rtf
dir : seeout

.         
.         reg dk_abortion i.t_w##c.pol_know i.round, cluster(respondent_id)

Linear regression                               Number of obs     =      9,620
                                                F(5, 4809)        =      39.43
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0281
                                                Root MSE          =     .14139

                        (Std. err. adjusted for 4,810 clusters in respondent_id)
--------------------------------------------------------------------------------
               |               Robust
   dk_abortion | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------+----------------------------------------------------------------
         1.t_w |   .0758362   .0077659     9.77   0.000     .0606114     .091061
      pol_know |  -.0017028   .0006596    -2.58   0.010     -.002996   -.0004096
               |
t_w#c.pol_know |
            1  |  -.0134027   .0021573    -6.21   0.000    -.0176319   -.0091734
               |
         round |
            2  |   .0017122   .0038401     0.45   0.656    -.0058161    .0092405
            3  |  -.0016299   .0035308    -0.46   0.644    -.0085518     .005292
               |
         _cons |   .0069813   .0034401     2.03   0.042     .0002372    .0137254
--------------------------------------------------------------------------------

.                 outreg2 using table_C1,  word  bd(3) sd(3) rd(3) alpha(0.01, 0.05, 0.1) symb
> ol(**, *, +)  lab append
table_C1.rtf
dir : seeout

.         
. 
.         
.                 ** measure of political knowledge
.         recode pol_know (0 1=1) (2 3=2) (4 5=3), g(pk3)
(6,402 differences between pol_know and pk3)

. 
.         
.         * Table C2
.         reg estate_tax_support t_w i.round, cluster(respondent_id)

Linear regression                               Number of obs     =      8,309
                                                F(3, 4794)        =       2.11
                                                Prob > F          =     0.0964
                                                R-squared         =     0.0007
                                                Root MSE          =     .49597

                      (Std. err. adjusted for 4,795 clusters in respondent_id)
------------------------------------------------------------------------------
             |               Robust
estate_tax~t | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         t_w |  -.0094149   .0052155    -1.81   0.071    -.0196398    .0008099
             |
       round |
          2  |  -.0244996   .0183811    -1.33   0.183     -.060535    .0115357
          3  |  -.0290709   .0175472    -1.66   0.098    -.0634715    .0053297
             |
       _cons |    .585428   .0129181    45.32   0.000     .5601026    .6107533
------------------------------------------------------------------------------

.                 outreg2 using table_C2,  word  bd(3) sd(3) rd(3) alpha(0.01, 0.05, 0.1) symb
> ol(**, *, +)  lab replace
table_C2.rtf
dir : seeout

.                 
.                 reg estate_tax_support i.t_w##i.pk3 i.round, cluster(respondent_id)

Linear regression                               Number of obs     =      8,309
                                                F(7, 4794)        =      12.02
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0163
                                                Root MSE          =     .49221

                      (Std. err. adjusted for 4,795 clusters in respondent_id)
------------------------------------------------------------------------------
             |               Robust
estate_tax~t | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
       1.t_w |  -.0401768   .0166956    -2.41   0.016    -.0729078   -.0074458
             |
         pk3 |
          2  |   .0342532   .0200416     1.71   0.087    -.0050377     .073544
          3  |   .1338593   .0205695     6.51   0.000     .0935336     .174185
             |
     t_w#pk3 |
        1 2  |   .0150702   .0185453     0.81   0.416    -.0212871    .0514275
        1 3  |   .0448671   .0179974     2.49   0.013      .009584    .0801502
             |
       round |
          2  |  -.0209409   .0182068    -1.15   0.250    -.0566346    .0147529
          3  |  -.0228755   .0174425    -1.31   0.190    -.0570707    .0113197
             |
       _cons |   .5180743   .0203759    25.43   0.000     .4781282    .5580203
------------------------------------------------------------------------------

.                 outreg2 using table_C2,  word  bd(3) sd(3) rd(3) alpha(0.01, 0.05, 0.1) symb
> ol(**, *, +)  lab append
table_C2.rtf
dir : seeout

.         
.         reg capital_gains_support t_w i.round, cluster(respondent_id)

Linear regression                               Number of obs     =      8,943
                                                F(3, 4799)        =       2.08
                                                Prob > F          =     0.1010
                                                R-squared         =     0.0011
                                                Root MSE          =     .49574

                      (Std. err. adjusted for 4,800 clusters in respondent_id)
------------------------------------------------------------------------------
             |               Robust
capital_ga~t | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         t_w |  -.0037472   .0036145    -1.04   0.300    -.0108333    .0033389
             |
       round |
          2  |  -.0378597   .0182179    -2.08   0.038    -.0735751   -.0021443
          3  |  -.0322027   .0173603    -1.85   0.064    -.0662368    .0018313
             |
       _cons |   .5895824   .0127823    46.13   0.000     .5645232    .6146415
------------------------------------------------------------------------------

.                 outreg2 using table_C2,  word  bd(3) sd(3) rd(3) alpha(0.01, 0.05, 0.1) symb
> ol(**, *, +)  lab append
table_C2.rtf
dir : seeout

.                 
.                 reg capital_gains_support i.t_w##i.pk3 i.round, cluster(respondent_id)

Linear regression                               Number of obs     =      8,943
                                                F(7, 4799)        =       1.89
                                                Prob > F          =     0.0664
                                                R-squared         =     0.0025
                                                Root MSE          =     .49551

                      (Std. err. adjusted for 4,800 clusters in respondent_id)
------------------------------------------------------------------------------
             |               Robust
capital_ga~t | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
       1.t_w |  -.0107778   .0113192    -0.95   0.341    -.0329687     .011413
             |
         pk3 |
          2  |   .0159538   .0199609     0.80   0.424    -.0231787    .0550864
          3  |   .0439129   .0206669     2.12   0.034     .0033964    .0844294
             |
     t_w#pk3 |
        1 2  |   .0046293   .0126209     0.37   0.714    -.0201135    .0293721
        1 3  |   .0102939   .0121866     0.84   0.398    -.0135975    .0341854
             |
       round |
          2  |  -.0365823   .0182064    -2.01   0.045    -.0722752   -.0008895
          3  |   -.030392   .0173743    -1.75   0.080    -.0644536    .0036697
             |
       _cons |   .5653707   .0202425    27.93   0.000     .5256862    .6050553
------------------------------------------------------------------------------

.                         outreg2 using table_C2,  word  bd(3) sd(3) rd(3) alpha(0.01, 0.05, 0
> .1) symbol(**, *, +)  lab append
table_C2.rtf
dir : seeout

.         
.         reg abortion_support t_w i.round, cluster(respondent_id)

Linear regression                               Number of obs     =      9,418
                                                F(3, 4801)        =       3.02
                                                Prob > F          =     0.0286
                                                R-squared         =     0.0002
                                                Root MSE          =     .42404

                      (Std. err. adjusted for 4,802 clusters in respondent_id)
------------------------------------------------------------------------------
             |               Robust
abortion_s~t | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         t_w |  -.0081265   .0027414    -2.96   0.003    -.0135009    -.002752
             |
       round |
          2  |  -.0042924   .0152457    -0.28   0.778     -.034181    .0255961
          3  |   .0039899    .014598     0.27   0.785    -.0246288    .0326087
             |
       _cons |   .2388052   .0108423    22.03   0.000     .2175493    .2600611
------------------------------------------------------------------------------

.                 outreg2 using table_C2,  word  bd(3) sd(3) rd(3) alpha(0.01, 0.05, 0.1) symb
> ol(**, *, +)  lab append
table_C2.rtf
dir : seeout

.                 
.                 reg abortion_support i.t_w##i.pk3 i.round, cluster(respondent_id)

Linear regression                               Number of obs     =      9,418
                                                F(7, 4801)        =       1.52
                                                Prob > F          =     0.1556
                                                R-squared         =     0.0003
                                                Root MSE          =     .42409

                      (Std. err. adjusted for 4,802 clusters in respondent_id)
------------------------------------------------------------------------------
             |               Robust
abortion_s~t | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
       1.t_w |  -.0201079    .009104    -2.21   0.027     -.037956   -.0022598
             |
         pk3 |
          2  |   .0022992   .0171501     0.13   0.893     -.031323    .0359213
          3  |  -.0074031   .0177283    -0.42   0.676    -.0421588    .0273525
             |
     t_w#pk3 |
        1 2  |    .015289   .0099025     1.54   0.123    -.0041245    .0347025
        1 3  |   .0137699   .0097814     1.41   0.159    -.0054061    .0329459
             |
       round |
          2  |   -.004291   .0152599    -0.28   0.779    -.0342075    .0256255
          3  |    .003705   .0146175     0.25   0.800    -.0249521     .032362
             |
       _cons |   .2405235   .0172172    13.97   0.000     .2067699    .2742771
------------------------------------------------------------------------------

.                         outreg2 using table_C2,  word  bd(3) sd(3) rd(3) alpha(0.01, 0.05, 0
> .1) symbol(**, *, +)  lab append
table_C2.rtf
dir : seeout

.         
.         
. 
.         * Figure C1
.         reg estate_tax_support i.t_w##i.pk3 i.round, cluster(respondent_id)

Linear regression                               Number of obs     =      8,309
                                                F(7, 4794)        =      12.02
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0163
                                                Root MSE          =     .49221

                      (Std. err. adjusted for 4,795 clusters in respondent_id)
------------------------------------------------------------------------------
             |               Robust
estate_tax~t | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
       1.t_w |  -.0401768   .0166956    -2.41   0.016    -.0729078   -.0074458
             |
         pk3 |
          2  |   .0342532   .0200416     1.71   0.087    -.0050377     .073544
          3  |   .1338593   .0205695     6.51   0.000     .0935336     .174185
             |
     t_w#pk3 |
        1 2  |   .0150702   .0185453     0.81   0.416    -.0212871    .0514275
        1 3  |   .0448671   .0179974     2.49   0.013      .009584    .0801502
             |
       round |
          2  |  -.0209409   .0182068    -1.15   0.250    -.0566346    .0147529
          3  |  -.0228755   .0174425    -1.31   0.190    -.0570707    .0113197
             |
       _cons |   .5180743   .0203759    25.43   0.000     .4781282    .5580203
------------------------------------------------------------------------------

.         margins, at(pk3=(1 2 3) t_w=(0 1)) saving("h3b_estate_w", replace)

Predictive margins                                       Number of obs = 8,309
Model VCE: Robust

Expression: Linear prediction, predict()
1._at: t_w = 0
       pk3 = 1
2._at: t_w = 0
       pk3 = 2
3._at: t_w = 0
       pk3 = 3
4._at: t_w = 1
       pk3 = 1
5._at: t_w = 1
       pk3 = 2
6._at: t_w = 1
       pk3 = 3

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .5029514   .0169883    29.61   0.000     .4696465    .5362562
          2  |   .5372045    .010634    50.52   0.000      .516357     .558052
          3  |   .6368107   .0115847    54.97   0.000     .6140993    .6595221
          4  |   .4627746   .0220834    20.96   0.000     .4194809    .5060682
          5  |   .5120979   .0125858    40.69   0.000      .487424    .5367718
          6  |    .641501    .012707    50.48   0.000     .6165895    .6664125
------------------------------------------------------------------------------
(file h3b_estate_w.dta not found)

.         
.         reg capital_gains_support i.t_w##i.pk3 i.round, cluster(respondent_id)

Linear regression                               Number of obs     =      8,943
                                                F(7, 4799)        =       1.89
                                                Prob > F          =     0.0664
                                                R-squared         =     0.0025
                                                Root MSE          =     .49551

                      (Std. err. adjusted for 4,800 clusters in respondent_id)
------------------------------------------------------------------------------
             |               Robust
capital_ga~t | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
       1.t_w |  -.0107778   .0113192    -0.95   0.341    -.0329687     .011413
             |
         pk3 |
          2  |   .0159538   .0199609     0.80   0.424    -.0231787    .0550864
          3  |   .0439129   .0206669     2.12   0.034     .0033964    .0844294
             |
     t_w#pk3 |
        1 2  |   .0046293   .0126209     0.37   0.714    -.0201135    .0293721
        1 3  |   .0102939   .0121866     0.84   0.398    -.0135975    .0341854
             |
       round |
          2  |  -.0365823   .0182064    -2.01   0.045    -.0722752   -.0008895
          3  |   -.030392   .0173743    -1.75   0.080    -.0644536    .0036697
             |
       _cons |   .5653707   .0202425    27.93   0.000     .5256862    .6050553
------------------------------------------------------------------------------

.         margins, at(pk3=(1 2 3) t_w=(0 1)) saving("h3b_cgt_w", replace)

Predictive margins                                       Number of obs = 8,943
Model VCE: Robust

Expression: Linear prediction, predict()
1._at: t_w = 0
       pk3 = 1
2._at: t_w = 0
       pk3 = 2
3._at: t_w = 0
       pk3 = 3
4._at: t_w = 1
       pk3 = 1
5._at: t_w = 1
       pk3 = 2
6._at: t_w = 1
       pk3 = 3

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .5425122   .0169178    32.07   0.000     .5093455    .5756789
          2  |    .558466   .0105941    52.71   0.000     .5376967    .5792353
          3  |   .5864251   .0118523    49.48   0.000     .5631891    .6096611
          4  |   .5317343   .0193487    27.48   0.000     .4938021    .5696666
          5  |   .5523174   .0114377    48.29   0.000     .5298943    .5747405
          6  |   .5859412   .0123546    47.43   0.000     .5617205    .6101619
------------------------------------------------------------------------------
(file h3b_cgt_w.dta not found)

.         
.         reg abortion_support i.t_w##i.pk3 i.round, cluster(respondent_id)

Linear regression                               Number of obs     =      9,418
                                                F(7, 4801)        =       1.52
                                                Prob > F          =     0.1556
                                                R-squared         =     0.0003
                                                Root MSE          =     .42409

                      (Std. err. adjusted for 4,802 clusters in respondent_id)
------------------------------------------------------------------------------
             |               Robust
abortion_s~t | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
       1.t_w |  -.0201079    .009104    -2.21   0.027     -.037956   -.0022598
             |
         pk3 |
          2  |   .0022992   .0171501     0.13   0.893     -.031323    .0359213
          3  |  -.0074031   .0177283    -0.42   0.676    -.0421588    .0273525
             |
     t_w#pk3 |
        1 2  |    .015289   .0099025     1.54   0.123    -.0041245    .0347025
        1 3  |   .0137699   .0097814     1.41   0.159    -.0054061    .0329459
             |
       round |
          2  |   -.004291   .0152599    -0.28   0.779    -.0342075    .0256255
          3  |    .003705   .0146175     0.25   0.800    -.0249521     .032362
             |
       _cons |   .2405235   .0172172    13.97   0.000     .2067699    .2742771
------------------------------------------------------------------------------

.         margins, at(pk3=(1 2 3) t_w=(0 1)) saving("h3b_abortion_w", replace)

Predictive margins                                       Number of obs = 9,418
Model VCE: Robust

Expression: Linear prediction, predict()
1._at: t_w = 0
       pk3 = 1
2._at: t_w = 0
       pk3 = 2
3._at: t_w = 0
       pk3 = 3
4._at: t_w = 1
       pk3 = 1
5._at: t_w = 1
       pk3 = 2
6._at: t_w = 1
       pk3 = 3

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .2405722   .0145053    16.59   0.000     .2121352    .2690093
          2  |   .2428714   .0091484    26.55   0.000     .2249363    .2608064
          3  |   .2331691    .010183    22.90   0.000     .2132058    .2531323
          4  |   .2204643   .0145521    15.15   0.000     .1919355    .2489931
          5  |   .2380524   .0092889    25.63   0.000     .2198419    .2562629
          6  |    .226831   .0101741    22.29   0.000     .2068852    .2467769
------------------------------------------------------------------------------
(file h3b_abortion_w.dta not found)

.         
.         
.         
. 
. preserve

. use "h3b_estate_w", clear
(Created by command margins; also see char list)

. g topic="Estate tax"

. save "h3b_estate_w", replace
file h3b_estate_w.dta saved

. restore

. 
. preserve

. use "h3b_cgt_w", clear
(Created by command margins; also see char list)

. g topic="Capital gains tax"

. save "h3b_cgt_w", replace
file h3b_cgt_w.dta saved

. restore

. 
. preserve

. use "h3b_abortion_w", clear
(Created by command margins; also see char list)

. g topic="Abortion"

. save "h3b_abortion_w", replace
file h3b_abortion_w.dta saved

. restore

. 
. 
. 
. use "h3b_estate_w", clear
(Created by command margins; also see char list)

. append using "h3b_cgt_w"
(variable topic was str10, now str17 to accommodate using data's values)
(label _term already defined)
(label _atopt already defined)

. append using "h3b_abortion_w"
(label _term already defined)
(label _atopt already defined)

. 
. 
. * add a little "jitter"
. replace _at2=.90 if _at2==1 & _at1==0
variable _at2 was byte now float
(3 real changes made)

. replace _at2=1.90 if _at2==2 & _at1==0
(3 real changes made)

. replace _at2=2.90 if _at2==3 & _at1==0
(3 real changes made)

. 
. 
. replace _at2=1.1 if _at2==1 & _at1==1
(3 real changes made)

. replace _at2=2.1 if _at2==2 & _at1==1
(3 real changes made)

. replace _at2=3.1 if _at2==3 & _at1==1
(3 real changes made)

. 
. twoway ///
> (scatter _margin _at2 if _at1==0, msymbol(O) mcolor(black) lcolor(black)) ///
> (scatter _margin _at2 if _at1==1, msymbol(O) mcolor(gray) lcolor(gray) lpattern(solid)) ///
> (rspike _ci_lb _ci_ub _at2 if _at1==0,  lcolor(black)  lwidth(medthick)) ///
> (rspike _ci_lb _ci_ub _at2 if _at1==1, lcolor(gray)  lwidth(medthick)), ///
> by(topic, r(1) note("") title("", size(large) position(11))) subtitle(,  size(medsmall)) ///
> scheme(plotplain) yline(.5) legend(pos(6) col(2) title("")  order(1 2) label(1 "No DK-option
> ") label(2 "DK-option")) xlabel(1 "Low" 2 "Med" 3 "High", labsize(medsmall)  labcolor(gray) 
> tlength(0.5)) xtick(1 2 3) ylabel(0.2(.1)0.7, labsize(medsmall) labcolor(gray)) xtitle("Poli
> tical knowledge", size(medsmall) color(gray)) ytitle("Policy support", size(medsmall) color(
> gray)) xsize(8)

. 
. graph export "figureC1.pdf",  replace
file /Users/qsg999/Desktop/PSRM_replication_material/temp/figureC1.pdf saved as PDF format

. 
. log close
      name:  <unnamed>
       log:  /Users/qsg999/Desktop/PSRM_replication_material/Appendix_C_log.log
  log type:  text
 closed on:  18 Jun 2024, 09:08:05
----------------------------------------------------------------------------------------------
